What types of IRR measurement methodologies are institutions expected to use < from the 2012 FAQ

Like many of the questions in the FAQ – this one is quite broad (the full question and answer from the FAQ are given below). The regulators’ answer to this one can probably be boiled down to this…banks should:

run earnings simulations that cover a 2-year time frame; but may possibly include from one to five years

to the extent possible model complex instruments separately

It probably should have been boiled down to those bullet points, but it wasn’t. Many of the finer points in the long drawn out answer have been lost. Almost everyone I talk to sees only one takeaway from this answer:

banks should run a 2-year earnings simulation

That’s it. That’s all we’re being asked for these days because our customers want to meet the “requirements” outlined by the FAQ.

In the text of the answer the regulators really emphasize the importance of using earnings simulations. However I think they clouded things a bit by talking about simulations over “various time frames”, “generally one to five years”, and “at least a two-year period”. They throw around phrases like “various time horizons”, “longer time horizons”, and “longer-term simulations” when they are talking about both earnings and EVE simulations. It’s hard to tell which one they mean. What is meant by long(er)-term? 3 years? 5 years? 7 years? Longer? Even I’m not really sure from their answer. Recently we’ve been deluged with questions about this one. The most popular request? Could we run a 2-year earnings and EVE simulation? Part of that request doesn’t even make sense!

The regulators also (intentionally or not) de-emphasized the use of EVE. They say that, “Although not expected for community institutions with less-complex balance sheets, longer-term simulations (five to seven years) are a useful tool to highlight option risk positions and better evaluate risk. Long-term simulations can provide a complementary metric to “risk-to-capital” measurements, allowing institutions to understand how interest rate shifts could affect future earnings over longer time horizons.” I think it was a mistake to say you can “better evaluate risk” with such a long-term forecast. Here are my two reasons:

Are there really community bankers out there that are discuss what their institution’s IRR profile will be five to seven years in the future? Probably so, but I would really be surprised to find that they are taking them seriously. They may be academically interesting, but I’d be quite skeptical of any specific community bank management plans based on such an analysis. Remember measuring earnings at risk requires a forecast. How good is anybody’s five to seven year forecast? The track records don’t look too good. (Even 2-year forecasts typically aren’t that good.)

They imply that EVE at risk measurements are not expected for community institutions. Bad move (especially in this current rate environment.) In fact the EVE at risk measurement can capture risk that you might not see in the earnings simulations. Better yet, it might expose risks that you’ve covered up (i.e. “modeled away”) in the earnings simulation. The possibility that a forecast may alter the earnings simulation stress-test is something the regulators mention in question #8 of the FAQ. EVE at risk measurements don’t have this problem so I’m surprised to see them imply that community banks are “not expected” to look at EVE at risk. (And before you start emailing to tell me…I know measuring EVE at risk has its own set of problems…that’s why banks should use both types.)

Here is the actual text from the document:

Question from the FAQ: 3) What types of IRR measurement methodologies are institutions expected to use?

Answer from the FAQ: Institutions should measure the potential impact of changes in market interest rates on both earnings and the economic value of capital. Measurement methodologies generally focus on either changes to net interest income (NII)/net income (NI), or changes to the economic value of capital over various time horizons. Income simulations are typically used to measure potential volatility in NII/NI over various time horizons (generally one to five years). Economic or market value of equity models typically cover much longer time horizons and measure risk to the economic value of capital. Institutions should use a combination of both earnings-focused and economic value of capital-focused measures to capture the full spectrum of IRR. Large and complex institutions as well as model vendors continue to develop new approaches to IRR measurement. Financial regulators will consider these new approaches on a case-by-case basis to ensure that they meet the spirit of outstanding guidance and effectively model IRR.

Since the original interagency guidance on IRR was issued by the FRB, FDIC, and OCC in 1996, the number and availability of financial products with embedded options has grown considerably. Such products, which include but are not limited to collateralized mortgage obligations, step-up notes, callable agency bonds, convertible Federal Home Loan Bank borrowings, alternative certificates of deposit, one-to-four family residential mortgage loans/securities, and commercial real estate loans/securities, present significant challenges to IRR measurement. The IRR measurement challenges arise because the timing and size of the cash flows may change considerably, depending on how interest rates vary over time. As a result, these products often carry significant prepayment or extension risk. The ability of risk measurement systems to capture the risk from these new products has also evolved over time. Institutions should manage the evolving risks in their on- and off-balance sheet positions, and a key part of this process is selecting the appropriate IRR measurement system and processes.

Institutions gain a better understanding of when rate and cash flow options may be exercised by using longer simulation time horizons. For example, significant levels of options risk embedded in assets and liabilities can cause large shifts in repricing cash flows over time. Depending on the type of scenario, and the nature of the options, these shifts may not become apparent until a simulation is projected beyond one year. This volatility in cash flows likely causes an institution’s earnings-at-risk profile to change significantly as the simulation progresses. To capture this potential “cliff effect,” exposures should be projected over at least a two-year period. To understand how risk evolves, management is encouraged to measure earnings-at-risk for each 12-month period over the simulation horizon. Although not expected for community institutions with less-complex balance sheets, longer-term simulations (five to seven years) are a useful tool to highlight option risk positions and better evaluate risk. Long-term simulations can provide a complementary metric to “risk-to-capital” measurements, allowing institutions to understand how interest rate shifts could affect future earnings over longer time horizons.

Institutions should measure the potential impact of changes in market interest rates on the economic value of capital. Measuring risk to capital generally requires institutions to use some type of long-term economic or market-value-based process. Risk to capital has traditionally been measured by analyzing the effects of various interest rate scenarios through either a long-term discounted cash flow model such as economic value of equity (EVE), net economic value (NEV), or models assessing anticipated changes in net present value (NPV) or duration.

When modeling complex products with embedded options, risk managers should not overlook the importance of data aggregation and stratification. Complex, or structured, securities should be modeled individually. Homogenous whole-loan portfolios, when possible should be aggregated by product type, coupon band, maturity, and prepayment volatility. For adjustable-rate portfolios, management should ensure that the modeling process takes into account all loan attributes that have a material impact on IRR, including reset dates, reset indices and margins, embedded caps and floors, and any prepayment penalties.